Mutation frequency. We trained several versions of RealiT 
by varying the mutation frequency (up to 1x, 3x, 5x, 10x, 100x and 1000x unique mutants per code snippet). For the comparison, we measured the performance of each trained model before and after fine-tuning on real bug fixes. The models are evaluated on our real bugs validation set. Figure REF  gives an overview of our results for bug localization and repair accuracy independently. The configuration 0x represents a version of RealiT  only trained on real bug fixes.
First of all, in contrast to common believe [1]}, we observe that increasing the number of mutants up to 100x generated mutants per code snippet leads to a performance improvement for both localization and repairWe observe the same trend for joint localization and repair which is not shown here for brevity.. This is surprising as the number of unique mutants per code snippet is limited (with an average of 85 unique mutants per code snippet) and, henceforth, buggy programs with more mutant candidates are oversampled. Still, we found that increasing the limit of mutants beyond 100x (and thereby oversampling code snippets in our dataset that provide up to 200k unique mutants) actually decreases the localization and repair performance.
